Model comparison
GLM-4.7 vs Yi-34B
GLM-4.7 is the stronger model overall, scoring 42.0 to 27.8 on the Noometry Index.
Last verified . 19 shared benchmarks.
Summary
- They share 19 benchmarks with published results for both. GLM-4.7 scores higher in 8 categories and Yi-34B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 7.5.
- The biggest single-benchmark swing is GPQA Diamond: 83.3% for GLM-4.7 and 14.7% for Yi-34B.
Side by side
| GLM-4.7 | Yi-34B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | 01.AI |
| Noometry Index | 42.0 | 27.8 |
| Released | 2025-12-22 | 2023-11-02 |
| Weights | Open | Open |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 36 | 23 |
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Category by category
Coding GLM-4.7 leads
GLM-4.7: 44.0 (#79), Yi-34B: 32.3 (#274)
| Benchmark | GLM-4.7 | Yi-34B |
|---|---|---|
| LMArena Coding | 1454 | 1112 |
| LMArena WebDev | 1435 | — |
| SciCode | 45.1% | — |
| ALE-Bench | 399.48 | — |
Agentic & Tool Use Not comparable
GLM-4.7: 26.5 (#103), Yi-34B: —
| Benchmark | GLM-4.7 | Yi-34B |
|---|---|---|
| Terminal-Bench | 33.4% | — |
| Vending-Bench 2 | 2,377 | — |
Reasoning GLM-4.7 leads
GLM-4.7: 24.3 (#164), Yi-34B: 21.2 (#226)
| Benchmark | GLM-4.7 | Yi-34B |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1104 |
| Epoch Capabilities Index | 143.51 | 117.39 |
| SimpleBench | 47.7% | — |
| CritPt | 1.7% | — |
| Chess Puzzles | 6% | — |
| BIG-Bench Hard | — | 71.7% |
Math GLM-4.7 leads
GLM-4.7: 38.6 (#135), Yi-34B: 21.6 (#282)
| Benchmark | GLM-4.7 | Yi-34B |
|---|---|---|
| LMArena Math | 1423 | 1114 |
| OTIS Mock AIME 2024-2025 | 83.3% | — |
| ProofBench | 6% | — |
| MATH Level 5 | — | 5.1% |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
| GSM8K | — | 76% |
Knowledge GLM-4.7 leads
GLM-4.7: 47.0 (#80), Yi-34B: 7.5 (#309)
| Benchmark | GLM-4.7 | Yi-34B |
|---|---|---|
| GPQA Diamond | 83.3% | 14.7% |
| LMArena Expert | 1424 | 1061 |
| SimpleQA Verified | 32.2% | — |
| Vectara Hallucination Rate | 11.7% | — |
| MMLU | — | 76.3% |
Multilingual GLM-4.7 leads
GLM-4.7: 52.8 (#79), Yi-34B: 29.7 (#264)
| Benchmark | GLM-4.7 | Yi-34B |
|---|---|---|
| LMArena Non-English | 1417 | 1079 |
| LMArena Chinese | 1495 | 1176 |
| LMArena French | 1432 | 1081 |
| LMArena German | 1424 | 1042 |
| LMArena Japanese | 1439 | 993 |
| LMArena Korean | 1399 | 959 |
| LMArena Russian | 1423 | 1050 |
| LMArena Spanish | 1434 | 1070 |
Instruction Following GLM-4.7 leads
GLM-4.7: 74.4 (#95), Yi-34B: 56.2 (#274)
| Benchmark | GLM-4.7 | Yi-34B |
|---|---|---|
| LMArena Instruction Following | 1411 | 1091 |
Long Context GLM-4.7 leads
GLM-4.7: 42.8 (#116), Yi-34B: 33.2 (#264)
| Benchmark | GLM-4.7 | Yi-34B |
|---|---|---|
| LMArena Longer Query | 1432 | 1094 |
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
Writing & Preference GLM-4.7 leads
GLM-4.7: 60.9 (#93), Yi-34B: 34.1 (#273)
| Benchmark | GLM-4.7 | Yi-34B |
|---|---|---|
| LMArena Text | 1435 | 1129 |
| LMArena Creative Writing | 1401 | 1108 |
| LMArena Multi-Turn | 1446 | 1113 |
| EQ-Bench Creative Writing | 1413 | — |
Frequently asked questions
Is GLM-4.7 better than Yi-34B?
GLM-4.7 is the stronger model overall, scoring 42.0 to 27.8 on the Noometry Index.
Is GLM-4.7 or Yi-34B better for coding?
GLM-4.7 scores higher on coding benchmarks: 44.0 versus 32.3 in the Noometry coding category.
How many benchmarks do GLM-4.7 and Yi-34B share?
19 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Yi-34B has 23.